Delayed leukocytosis after hard strength and endurance exercise: Aspects of regulatory mechanisms

Background  

During infections, polymorphonuclear neutrophilic granulocytes (PMN) are mobilized from their bone marrow stores, travel with blood to the affected tissue, and kill invading microbes there. The signal(s) from the inflammatory site to the marrow are unknown, even though a number of humoral factors that can mobilize PMN, are well known. We have employed a standardized, non-infectious human model to elucidate relevant PMN mobilizers. Well-trained athletes performed a 60-min strenuous strength workout of leg muscles. Blood samples were drawn before, during and just after exercise, and then repeatedly during the following day. Cortisol, GH, ACTH, complement factors, high-sensitive CRP (muCRP), IL-6, G-CSF, IL-8 (CXCL8) and MIP-1β (CCL4) were measured in blood samples. PMN chemotaxins in test plasma was assessed with a micropore membrane technique.     

A General and Dynamic Species Abundance Model, Embracing the Lognormal and the Gamma Models

One aspect of community ecology that has been given particular attention is the pattern of species abundances in a community. The species may have a wide range of abundances; some are very common and others rare. When species abundance models are fitted to observations, the lognormal model and one of the gamma models (e.g., the log-series model) are usually applied. The model that gives the best fit according to some goodness-of-fit test is then chosen. By applying a diffusion approximation for each species' dynamics with density regulation of the straight theta-logistic type, we here present a general species abundance model that embraces the two most widely applied species abundance models, the lognormal and the gamma. Our general model will, therefore, provide a better fit than the two special cases, except when it corresponds to one of them. In contrast to the classical models, ours is also dynamic, making it possible to evaluate the fluctuations in species abundance over time through both biotic and abiotic factors. The model is fitted to several species abundance data sets and our results compared to previous attempts to fit a model, usually either the lognormal or the log-series.     

Environmental stochasticity and extinction risk in a population of a small songbird, the great tit

Using a long-term demographic data set, we estimated the separate effects of demographic and environmental stochasticity in the growth rate of the great tit population in Wytham Wood, United Kingdom. Assuming logistic density regulation, both the demographic (sigma2d = 0.569) and environmental (sigma2e = 0.0793) variance, with interactions included, were significantly greater than zero. The estimates of the demographic variance seemed to be relatively insensitive to the length of the study period, whereas reliable estimates of the environmental variance required long time series (at least 15 yr of data). The demographic variance decreased significantly with increasing population density. These estimates are used in a quantitative analysis of the demographic factors affecting the risk of extinction of this population. The very long expected time to extinction of this population (approximately 10(19) yr) was related to a relatively large population size (>/=120 pairs during the study period). However, for a given population size, the expected time to extinction was sensitive to both variation in population growth rate and environmental stochasticity. Furthermore, the form of the density regulation strongly affected the expected time to extinction. Time to extinction decreased when the maximum density regulation approached K. This suggests that estimates of viability of small populations should be given both with and without inclusion of density dependence.     

Effects of NaHCO3 loading on acid-base balance, lactate concentration, and performance in racing greyhounds

This investigation examined the effects ofNaHCO₃ loading on lactateconcentration ([La]), acid-base balance, and performance for a 603.5-m sprint task. Ten greyhounds completed aNaHCO₃ (300 mg/kg body weight) andcontrol trial in a crossover design. Results are expressed as means ± SE. Presprint differences (P < 0.05) were found for NaHCO₃ vs.control, respectively, for blood pH (7.47 ± 0.01 vs. 7.42 ± 0.01), HCO₃ (28.4 ± 0.4 vs. 23.5 ± 0.3 meq/l), and base excess (5.0 ± 0.3 vs. 0.2 ± 0.3 meq/l). Peak blood [La] increased(P < 0.05) inNaHCO₃ vs. control (20.4 ± 1.6 vs. 16.9 ± 1.3 mM, respectively). Relative to control,NaHCO₃ produced a greater(P < 0.05) reduction in blood baseexcess (18.5 ± 1.4 vs. 14.1 ± 0.8 meq/l) andHCO₃ (17.4 ± 1.2 vs.12.8 ± 0.7 meq/l) from presprint to postexercise. Postexercise peak muscle H⁺concentration ([H⁺])was higher (P < 0.05) inNaHCO₃ vs. control (158.8 ± 8.8 vs. 137.0 ± 5.3 nM, respectively). Muscle[H⁺] recoveryhalf-time (7.2 ± 1.6 vs. 11.3 ± 1.6 min) and time to predosevalues (22.2 ± 2.4 vs. 32.9 ± 4.0 min) were reduced(P < 0.05) inNaHCO₃ vs. control, respectively.No differences were found in blood[H⁺] or blood[La] recovery curves or performance times.NaHCO₃ increased postexerciseblood [La] but did not reduce the muscle or blood acid-basedisturbance associated with a 603.5-m sprint or significantly affectperformance.

     

Alcohol Induced Alterations to the Human Fecal VOC Metabolome

Studies have shown that excessive alcohol consumption impacts the intestinal microbiota composition, causing disruption of homeostasis (dysbiosis). However, this observed change is not indicative of the dysbiotic intestinal microbiota function that could result in the production of injurious and toxic products. Thus, knowledge of the effects of alcohol on the intestinal microbiota function and their metabolites is warranted, in order to better understand the role of the intestinal microbiota in alcohol associated organ failure. Here, we report the results of a differential metabolomic analysis comparing volatile organic compounds (VOC) detected in the stool of alcoholics and non-alcoholic healthy controls. We performed the analysis with fecal samples collected after passage as well as with samples collected directly from the sigmoid lumen. Regardless of the approach to fecal collection, we found a stool VOC metabolomic signature in alcoholics that is different from healthy controls. The most notable metabolite alterations in the alcoholic samples include: (1) an elevation in the oxidative stress biomarker tetradecane; (2) a decrease in five fatty alcohols with anti-oxidant property; (3) a decrease in the short chain fatty acids propionate and isobutyrate, important in maintaining intestinal epithelial cell health and barrier integrity; (4) a decrease in alcohol consumption natural suppressant caryophyllene; (5) a decrease in natural product and hepatic steatosis attenuator camphene; and (6) decreased dimethyl disulfide and dimethyl trisulfide, microbial products of decomposition. Our results showed that intestinal microbiota function is altered in alcoholics which might promote alcohol associated pathologies.     

ESTIMATING PHENOTYPIC SELECTION IN AGE‐STRUCTURED POPULATIONS BY REMOVING TRANSIENT FLUCTUATIONS

An extension of the selection differential in the Robertson–Price equation for the mean phenotype in an age‐structured population is provided. Temporal changes in the mean phenotype caused by transient fluctuations in the age‐distribution and variation in mean phenotype among age classes, which can mistakenly be interpreted as selection, will disappear if reproductive value weighting is applied. Changes in any weighted mean phenotype in an age‐structured population may be decomposed into between‐ and within‐age class components. Using reproductive value weighting the between‐age class component becomes pure noise, generated by previous genetic drift or fluctuating selection. This component, which we call transient quasi‐selection, can therefore be omitted when estimating age‐specific selection on fecundity or viability within age classes. The final response can be computed at the time of selection, but can not be observed until lifetime reproduction is realized unless the heritability is one. The generality of these results is illustrated further by our derivation of the selection differential for the continuous time age‐structured model with general age‐dependent weights. A simple simulation example as well as estimation of selection components in a house sparrow population illustrates the applicability of the theory to analyze selection on the mean phenotype in fluctuating age‐structured populations.     

Complete mitochondrial genome sequence of the Arctic gammarid,Onisimus nanseni (Crustacea; Amphipoda): Novel gene structures and unusual control region features

To analyze the mitogenome of the amphipod Onisimus nanseni, we amplified the complete mitogenome of O. nanseni using long-PCR and genome walking techniques. The mitogenome of O. nanseni is circular and contains all the typical mt genes (2 rRNAs, 22 tRNAs, and 13 protein-coding genes). It has two peculiar non-coding regions of 148 bp and 194 bp. The latter can be involved in replication and termination processes. The total length of the pooled protein-coding, rRNA, and tRNA genes is shorter than those of other crustaceans. In addition, the intergenic spacers of the O. nanseni mitogenome are considerably shorter in length than those of other crustaceans. Fourteen adjacent genes overlap, resulting in a compact mitogenomic structure. In the O. nanseni mitogenome, the AT composition is elevated, particularly in the control regions (78.9% AT), as has been demonstrated for two other amphipods. The tRNA order is highly rearranged compared to other arthropod mitogenomes, but the order of protein-coding genes and rRNAs is largely conserved. The gene cluster between the CO1 and CO3 genes is completely conserved among all amphipods compared. This provides insights into the evolution and gene structures of crustacean mitochondrial genomes, particularly in amphipods.     

Post-translational Modifications Differentially Affect IgG1 Conformation and Receptor Binding

Post-translational modifications (PTMs) can have profound effects on protein structure and protein dynamics and thereby can influence protein function. To understand and connect PTM-induced functional differences with any resulting conformational changes, the conformational changes must be detected and localized to specific parts of the protein. We illustrate these principles here with a study of the functional and conformational changes that accompany modifications to a monoclonal immunoglobulin γ1 (IgG1) antibody. IgG1s are large and heterogeneous proteins capable of incorporating a multiplicity of PTMs both in vivo and in vitro. For many IgG1s, these PTMs can play a critical role in affecting conformation, biological function, and the ability of the antibody to initiate a potential adverse biological response. We investigated the impact of differential galactosylation, methionine oxidation, and fucosylation on solution conformation using hydrogen/deuterium exchange mass spectrometry and probed the effects of IgG1 binding to the FcγRIIIa receptor. The results showed that methionine oxidation and galactosylation both impact IgG1 conformation, whereas fucosylation appears to have little or no impact to the conformation. FcγRIIIa binding was strongly influenced by both the glycan structure/composition (namely galactose and fucose) and conformational changes that were induced by some of the modifications.The structure of many proteins can be altered by post-translational modifications (1). Although the impact of post-translational modifications (PTMs)¹ on protein structure is more understood for some modifications (e.g. phosphorylation; see Ref. 2), it is less defined for other PTMs and in many cases is protein-dependent. Because there are many important downstream effects of PTMs, including changes in protein localization, protein and cellular diversification, protein functionality, protein stability, protein life cycle, and so forth, understanding how PTMs alter protein structure for as many proteins as possible in a timely manner is a highly desirable goal. Furthermore, in an age where recombinant proteins are being used to treat disease, it becomes ever more important to understand how particular modifications may alter the structure and eventually the function of therapeutic proteins. To realize these goals, methods that permit access to conformational information for modified forms of therapeutic proteins must be developed and refined. In this report, we will illustrate how MS can contribute to structural proteomics by describing our recent work with a recombinant monoclonal antibody (an IgG1), which represents an important class of therapeutic proteins.Many biopharmaceutical companies are pursuing antibody drugs (3). In particular, the IgG1 subclass of antibodies has evolved into a commonly used therapeutic option for the treatment of a wide range of diseases. IgG1s consist of a dimer of identical heavy chains and light chains that fold to form (from N to C terminus) the variable, CL, CH1, CH2, and CH3 domains (as an example, see Ref. 4). Individual domains are structurally stable and are primarily composed of antiparallel β-sheets arranged in an immunoglobulin-like β-sandwich (5). The variable, CL, and CH1 domains are collectively referred to as the Fab (fragment antigen binding) portion of IgG1, which is responsible for recognizing a specific antigen. The CH2 and CH3 domains together are referred to as the Fc (fragment crystallizable) portion, which carries out effector functions such as binding to Fcγ receptors. These effector functions are essential to many therapeutic antibodies, especially when antibody-dependent cell-mediated cytotoxicity and complement-dependent cytotoxicity are involved in the mechanisms of action (6).As a biopharmaceutical, IgG1 monoclonal antibodies are critically monitored throughout production (7). In many cases, the impact of structural modifications in these and other formulated versions of biopharmaceuticals are not well understood at a functional level. In the case of IgG1s, with over 1300 amino acid residues and a molecular mass approaching 150 kDa, a large array of PTMs can be incorporated both in vivo (during cellular synthesis) and in vitro (as a result of handling and processing steps that occur during purification, vialing, and storage). Commonly monitored PTMs on IgG1s include methionine oxidation, asparagine and glutamine deamidation, N-terminal acetylation or cyclization, glycation of lysine, and variable glycosylation (8). Some of these modifications affect only a small percentage of the protein product, and their presence may not change overall outcome. Others, however, can have significant impact on the structure, function, and biological activities of a protein that can involve self-association as well as interactions with other proteins (9). The same PTMs can affect different IgG1 molecules in different ways or have no effect(s) at all. Therefore assessing the presence of PTMs, determining the relative level of the modifications, and understanding the structural effects of PTMs are all important during development of protein biopharmaceuticals.Two commonly studied IgG1 modifications are methionine oxidation and glycosylation, each of which has been shown to affect biological function (6, 10). Methionine oxidation has been implicated in protein stability (inducing aggregation), and increased oxidation levels have been shown to provoke an immunogenic response (11–13). Elevated levels of methionine oxidation in an IgG1 were shown to impact neonatal Fc receptor (FcRn) and protein A binding (10). Variable glycosylation (i.e. different levels of sialic acid, galactose, fucose, or high mannose structures) is known to influence thermal stability and effector functions (14–16). Previous studies have shown that removal of fucose from the glycan present on the Fc portion of an IgG1 can greatly enhance Fc binding to FcγRIIIa, but removal of the entire glycan nearly abolishes FcγRIIIa binding (17). As oxidation and changes to the glycan are both common IgG1 modifications, we were interested in determining the conformational effects of oxidation, afucosylation, and galactosylation and correlating any conformational changes that were observed with changes of FcγRIIIa binding activity.Conformational analysis of large proteins like antibodies, however, is not trivial. Traditional biophysical techniques such as circular dichroism, DSC, and fluorescence provide useful information, but these techniques look at the entire protein and provide only a global view (18). NMR and x-ray crystallography can both provide high resolution structural analysis, but each is faced with limitations that often make the study of an intact IgG1 difficult or nearly impossible (19–21). Recently we described how hydrogen/deuterium exchange (H/DX) MS could be used to study the conformation and conformational dynamics of an intact IgG1 with resolution down to stretches of several amino acid residues (22). For the present work, we used H/DX MS to study the impact of galactosylation, oxidation, and afucosylation on the conformation and dynamics of an intact IgG1. We also studied the complex of IgG1 and FcγRIIIa to map the points of interaction and probe any changes in the dynamics of the IgG1 as a result of FcγRIIIa interaction. Finally, we correlated the functional activity of all the proteins that were studied by H/DX MS with the observed conformational disturbance(s). Such correlations are important to connect structure with function and to understand whether a particular PTM is something that may affect the therapeutic value of a recombinant protein.     

Heterogeneity in dynamic species abundance models: the selective effect of extinction processes

There is often large variation in traits across the species of a community. In particular, variation in life history traits affecting population dynamics is likely to affect the species abundance distribution. Applying a dynamic and heterogeneous species abundance model we study how differences in extinction time for species in a community act as a force changing the distribution of dynamic parameters across species. This process may generate communities that are more heterogeneous then the heterogeneity measured as the species enter the community. Analytical results for some versions of the lognormal and gamma species abundance model are given as exemplifications of this process, together with stochastic simulations demonstrating the temporal changes in number of species and community heterogeneity through time.     

Heterogeneous communities with lognormal species abundance distribution: Species-area curves and sustainability

Heterogeneous species abundance models are models in which the dynamics differ between species, described by variation among parameters defining the dynamics. Using a dynamic and heterogeneous species abundance model generating the lognormal species abundance distribution it is first shown that different degrees of heterogeneity may result in equivalent species abundance distributions. An alternative to Preston's canonical lognormal model is defined by assuming that reduction in resources, for example reduction in available area, increases the density regulation of each species. This leads to species-individual curves and species-area curves that are approximately linear in a double logarithmic plot. Preston's canonical parameter gamma varies little along these curves and takes values in the neighborhood of one. Quite remarkably, the curves, which define the sensitivity of the community to area reductions, are independent of the heterogeneity among species for this model. As a consequence, the curves can be estimated from a single sample from the community using the Poisson lognormal distribution. It is shown how to perform sensitivity analysis with respect to over-dispersion in sampling relative to the Poisson distribution as well as sampling intensity, that is, the fraction of the community sampled. The method is exemplified by analyzing three simulated data sets.